The Tropical Coral Reef Line Fishery is a multispecies hook and line fishery that occurs predominantly in coral reef or shoal habitats within the Great Barrier Reef Marine Park. The reef line fishery has three major sectors: (i) commercial fishing, (ii) commercial charter fishing, and (iii) recreational fishing. The commercial sector of the fishery is spread along the entire length of the Great Barrier Reef system, with vessels that come predominantly from six ports: Cooktown, Cairns, Townsville, Bowen, Mackay and Gladstone. The main target species for all sectors of the fishery are coral trout, red throat emperor and red emperor.
The commercial reef fish catch is approximately 1600 to 2400 tonnes per annum.
Only 361 to 416 primary reef line boats reported landing reef species between 1989 and 1994. The current analysis of the reef line fishery estimates that in 1996, 1,149 tonnes of reef fish were caught by vessels
catching >500kg coral trout per year. This represents a total gross value in 1996 of nearly $21 million that suggests that the KPMG (1999) 1996 estimate of $17million for the whole commercial fishery may be a significant underestimate. The 'dedicated' reef line vessels catching >5000kg of coral trout per year caught the majority (81%) of the reef fish catch in 1996. The total 1996 catch of 927 tonnes by this group represented a total gross value of $15 million.
Profitability and catch rates were extremely variable both spatially and temporally for vessels within the fishery. Hence, a skipper's short run decisions of whether or not to go fishing, where to fish, and what target to pursue will have a direct impact on the profitability of fishing. Understanding fishing strategies is important both as part of a general understanding of the dynamics of the fishery and in predicting how a fishery might respond to proposed management changes, such as
effort or area restrictions. The current study is a description of the commercial reef line fishery and an investigation of the short run decisions or fishing strategies of commercial reef line fishermen. Using information gathered from a skipper interview program and applying it to the commercial catch and effort logbook records, the analysis uses a number of modelling techniques to identify the factors that influence a fisherman's decision on where to fish.
The average dedicated reef line fisherman was middle aged, an owner-operator having on average at least eight years experience in the reef line fishery and expecting to remain in the fishery for a further ten years or longer. The primary vessel was the fisherman's major investment in the fishery and was, on average, 20 years old. Commonly, four crew each fish from his or her own dory. The size and construction of dories was standard across the fishery. Fishing was conducted with relatively standard gear
and in similar depths by all fishing operations. Fish were either killed upon capture to be processed as frozen fillets or whole fish, or retained alive and sold as live fish for the export market. The average length of a fishing trip was 12 days, being determined largely by weather or when a desired catch was reached. The selection of areas to fish upon leaving port was made on the basis of previous knowledge of wind and tides in the region and past catch rates. Decisions on whether to fish a reef were made largely on the basis of previous catch rates. Information about where fish may be was primarily sourced from their own records, or in some cases, from discussions with other fishermen.
Estimates of net revenue, total economic costs, financial and economic profitability and return on capital, suggest that the short-term viability of most vessels, whether large or small, L2 or L3 endorsed, is quite stable. There was marked difference in earned revenue
between vessel groups but all had positive total net receipts. Net return was most pronounced in the larger vessels and the >5000kg CT vessel group. Rates of return on invested capital suggested that the long run viability for many vessel groups was not stable. An investigation of supplementary revenue earned by firms from other fishing endorsements suggested only 20% of >500kg CT vessels earned other income from fishing. For the more dedicated vessel groups (>5000kg CT), the return on capital was positive, indicating long term viability.
Most of the fishing technology was directed at catching coral trout. Although there was slight evidence for jointness-in-inputs between coral trout and red throat emperor, the latter species could be considered a complementary product. These two factors, standard fishing technology and the largely single species focus of the fishery, suggested that management of the reef line fishery can occur at the
fishery level, rather than requiring individual species management plans.
The spatial effort allocation from 1992 to 1996 in the Mackay region of the fishery suggested that fishing effort in most grids was not being allocated optimally, with the observed levels being greater than the estimated optimal effort. The effort levels did not approach, however, Gordon's bionomic equilibrium where the profit maximising behaviour of individual fishing firms had collectively driven short-run rents to zero. The high variability in the observed effort levels and the average net returns across grids suggested that effort allocation by fishermen can be quite complex. Subsequently, site selection and harvest may be in accordance with many different strategies. For example, fishing firms may minimise cost, maximise expected utility or minimise variability in expected returns rather than simply follow the primary objective of profit maximisation.
dynamic environment in which the reef line fishery operates, the success of information acquisition and sharing between fishermen could vary enormously from one fisherman to the next. The high level of uncertainty dictates that expectations of returns across reefs are very difficult to form and validate. In the absence of complete control over effort, understanding the response of fishers to changes in biological, economic and regulatory conditions in fisheries is critical to designing management plans that will protect the resources and provide economic benefits to fishers and consumers.
Models that test for the sensitivity of movement to changes in variables within the skippers' utility functions were used to explain the spatial allocation of effort across the whole fishery. Discrete choice frameworks were employed to develop a behavioural model of fishing site selection based on a conceptual model of fishing behaviour derived from interviews with fishing
skippers. The model was applied to existing commercial fishing catch and effort data to explain the spatial allocation of fishing effort by dedicated reef line fishermen in the Mackay Region of the Great Barrier Reef.
Although the explanatory powers of both the non-nested conditional logit model and nested multinomial logit models were low, they provided some interesting insights into how fishing sites were selected. The results suggested that fishermen chose large areas to fish, based on their recent average value per unit of effort, and would return to areas they knew well. Within those large areas, fishing sites were chosen on the basis of average value per unit of effort over a longer time period, in this case, the previous six months. The elasticities showed, however, a strong tendency for fishermen to return to similar fishing locations based on receiving higher average catch rates at fishing sites they had previously fished, rather than simply returning
to areas out of tradition or other non-pecuniary reasons. Returning to areas that provided higher catch rates in the past may also explain the risk seeking behaviour displayed by fishermen returning to grids with high variability. These results suggest that fishermen were choosing fishing sites within the large areas where they had high catches in the past even though the variability of past value per unit of effort was large. The results of the nested discrete choice model suggest that a skipper's experience of particular fishing locations and his knowledge of past catch rates underlies his decision to fish there in the future.
The results strongly suggest that fishing patterns are individualistic. The nested model found that fishermen appear to avoid the remainder of the fleet, selecting not to fish in large areas where the fleet had operated during the previous month. The results also suggested there was little information sharing and fishermen were unaware
of what the rest of the fleet was doing until some considerable time had elapsed.
Co-operative behaviours are difficult to recognise in the reef line fishery because of the tendency for individual fishing patterns. Individual fishing patterns, on the other hand, may well be a competitive behaviour leading to optimal effort allocation. It is reasonable to assume that any risk averse fisher in deciding where to fish, would use, beside his own records, fleet information on expected catch rates and variances in net returns at each location. Portfolio theory was applied to spatial allocation of effort to investigate whether fishing firms base their choice of fishing grids on the expected returns and variability in returns of their own catch rate in comparison to the average catch rate for the fleet. The efficient portfolio of fishing site alternatives over which effort was allocated was determined for each fishing firm. The efficient portfolio was compared to each
firm's actual spatial effort allocation over four years. The portfolio analysis suggested that the majority of vessels disregard the performance of the fleet altogether. Most vessels did not seek to minimise variance in expected catch rates by taking into consideration the difference between their catch and the average for the remainder of the fleet in each fishing location. The results confirm the discrete choice modelling that most vessels act as individuals preferring to base their decisions on their own experience with little regard for the remainder of the fleet.
The coral reef environment in which decisions are made is dynamic and dangerous. Consequently, the information is complex with very short time decay. Thus fishermen can know only a limited area well instead of the whole fishing ground. This restricts their mobility as they tend to go back to areas they know rather than concern themselves with what the fleet may be doing elsewhere. Hence
individual fishermen may not readily have access to information about other fishers' catches in other areas. Additionally, they may not actively seek out other information in the event that they will be lured to search in unfamiliar areas. These searches could be based on unreliable information of past catches under previous weather and sea conditions that have since changed. Calculating variability in expected returns is difficult as fishermen have little context in which to make these decisions for an area they have not visited often. Maintaining social standing is still probably a motivator, but in the sense of knowing your own patch well rather than trying to achieve fleet average catches across the entire fishing grounds.
Whereas the fishing strategies exhibited by reef line fishermen may not be greatly affected by catch restrictions imposed by fisheries management, these fishing behaviours do have significant implications for marine park management.
Zoning plans that restrict certain activities around single or groups of reefs form the basis of marine park planning. Significant hardship may be imposed on some operators if closures include reefs on certain fishermen's fishing paths. In this respect, poorly planned reef closures could be inequitable. Additionally, dislocation of fishermen from areas with which they are familiar could further impose hardship if several years are required before displaced fishermen accumulate sufficient knowledge of their new fishing territory to recover previous economic returns. Spatial models of fishing site selection highlight the scales of management that must be applied in coral reef environments when integrating marine park conservation and fisheries management objectives.